Qualitative description & statistics Flashcards

1
Q

discrete variables

A

dichotomous = binary (female/male)
categorical = nominal ( bus, bike, walk)
ordinal ( very satisfied –> neutral –> dissatisfied)

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2
Q

discrete variables

A

dichotomous = binary (female/male)
categorical = nominal ( bus, bike, walk)
ordinal ( very satisfied –> neutral –> dissatisfied)

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3
Q

interval (i.e. differences are meaningful) = numerical

A

count
ratio ( height)
continuous (time)

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4
Q

measurement

A

precision vs accuracy
significant figures

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5
Q

describing distributions

A

univariate or bivariate

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6
Q

univariate

A

normal
uniform
bimodal
U-shaped
skewed

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7
Q

descriptive stats

A

measures of central tendency
measures of variation
shape ( higher moments)

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8
Q

measures of central tendency

A

mean, median, mode

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9
Q

measures of variation

A

range, variance and standard deviation, quantiles, percentiles, inter-quartile

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10
Q

shape (higher moments)

A

variance, skewness, kurtosis

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11
Q

confidence

A

standard error
confidence interval ( credible interval)
statistical significance
scientific/ economic/ clinical significance

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12
Q

likert scale example

A

strongly disagree–> disagree–> neutral –> agree –> strongly agree
( this data is categorical, ordinal, dichotomous, continuous)

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13
Q

accuracy

A

true. consistent with the truth or objective (unbiased)

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14
Q

precise

A

detailed, specific, having low uncertainty, highly resolved

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15
Q

measurement e.g. the flood water is 35 cm deep, plus or minus half a cm

A

when we measure something in science, we always provide an estimate of our confidence along with the measurement

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16
Q

estimation e.g. ospreys live on average 38.4 +/- 5 years

A

when we statistically estimate something that was not measured directly, or infer something about the world through our research methods, we must also calculate a measure of confidence for what we report

17
Q

communicating precision = probabilistic statements

A

between 31% and 37% with 95 % confidence ( i.e., e [31%,37%] 19 times out of 20)

18
Q

displaying univariate qualitative (categorical) data

A

tables, bar charts, pie charts

19
Q

displaying univariate continuous data

A

histogram, box plot, kernel density estimation (carpet plot)

20
Q

bivariate plots: two categorical variable

A

paired bar plots

21
Q

how to visualize –> bivariate plots : one categorical, one continuous variable

A

multiple histograms, box plots

22
Q

visualize –> bivariate plots: two continuous variables

A

scatter plots

23
Q

univariate measures of dispersion

A

range
standard deviation: average distance from the mean, coefficient of variation, index of dispersion, interquartile range

24
Q

measures of shape

A

variance, skewness, kurtossis, L-moments

25
Skewness Left (negative), Right (positive)
(a) negative direction ( mean - median - mode) (b) positive direction ( mode -median-mean)
26
confidence interval
the range within which we would expect the value of the statistics to fall, if we were to repeat the study with a very large sample
27
what does confidence depend on?
sample spread, sample size, ( the nature of the statistic you're estimating )
28
credible intervals are a simpler concept from bayesian stats
the interval within which an unobserved parameter value falls with a particular probability, given available data, model, and preexisting knowledge - best estimate of the true value of parameter
29
properties of a univariate variable
ex: describe (aspects of) the distribution of an unordered list of sample measurements
30
multivariate properties
-two things measured for each individual sampled - describes (aspects of) the relationship between theme
31
univariate measures of central tendency
mean, median, mode
32
statistical significance
"within 3%, 19 times out of 20" - closely related to confidence intervals = error bars
33
scientific ( or economic) significance
an estimate of effect size put into context, for instance by competing effects, natural variation, or comparison to other costs or impacts